Contextual Information Acquisition and Management Solutions for IPBased Networks: A Survey

According to the ITU-T, Next Generation Networks (NGNs) are envisioned as IP-based networks capable of offering their users ubiquitous access to a multitude of feature rich, QoS-enabled, broadband services that combine telecom and datacom flavors. As NGNs continue to evolve, several challenges related to their operation and architecture are being investigated. One of these challenges is the enabling of innovative and personalized “killer” applications that would appeal to users and increase network operators’ revenues. Another challenge consists in the support of advanced QoS schemes that would take into consideration users’ needs and the network situation to manage the network resources in an efficient and adaptive manner. Context-awareness implies the ability to use contextual (or situational) information to provide relevant information and-or services to the user. The introduction of the context-awareness concept in NGNs could open the door to personalized, adaptive killer applications as well as context-aware dynamic QoS schemes. This paper surveys the literature on contextual information acquisition and management solutions-patents that were proposed for IP-based networks, evaluates their suitability with respect to context-awareness’ integration in NGNs, and discusses research directions. Among the evaluated solutions and patents, the 3GPP presence framework shows signification potential for context-awareness’ integration in NGNs. However, several open issues remain unsolved, such as: the definition of a standard and unified interface enabling the interaction with heterogeneous sensors; the definition of an expressive information model enabling the representation of a wide range of contextual information captured by physical-logical-mobile sensors; the usage of complementary approaches such as mobile and participatory sensing to achieve better processing capabilities on sensor nodes; and the definition of suitable business models and support functions regulating the interaction between sensors and NGNs.